M

Machine Learning

https://github.com/Lightning-AI/lightning-Habana Lightning support for Intel Habana accelerators.

🔧🔗https://github.com/takara-ai/go-attention

A full attention mechanism and transformer in pure go.

🔧🔗https://gitlab.com/gitlab-org/modelops/mlops/gitlab-mlops

A Python client for integrating GitLab's MLOps features, specifically designed to leverage GitLab's experiment tracking and model registry capabilities. This client simplifies the management of machine learning workflows by combining MLflow's flexibility with GitLab's powerful MLOps tools.

🔧🔗https://github.com/takara-ai/SwarmFormer

A pytorch implementation of SwarmFormer for text classification.

🔧🔗https://github.com/jennyzzt/LLM_debate_on_ARC

LLM Debate on ARC dataset

https://github.com/princeton-nlp/CharXiv CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs

🔧🔗https://github.com/pytorch/pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

🔧🔗https://github.com/lutzroeder/netron Visualizer for neural network, deep learning and machine learning models

https://github.com/Upsonic/On-Prem Self-Driven Autonomous Python Libraries

🔧🔗https://github.com/huggingface/speech-to-speech

Speech To Speech: an effort for an open-sourced and modular GPT4-o

🔧🔗https://github.com/SaintsSec/Navi

An Interface for AI built for cybersecurity professionals

🔧🔗https://github.com/takara-ai/SwarmFormer-C

Full C implementation of the SwarmFormer model architecture.

🔧🔗 meta-llama/llama-recipes Scripts for fine-tuning Meta Llama with composable FSDP & PEFT methods to cover single/multi-node GPUs.

🔧🔗https://github.com/IAHispano/Audio-Upscaler Versatile AI-driven audio upscaler to enhance the quality of any audio.

https://github.com/mlc-ai/mlc-assistant Chat with your documents and improve your writing using large-language models within your browser.

🔧🔗https://github.com/poloclub/diffusion-explainer

Diffusion Explainer: Visual Explanation for Text-to-image Stable Diffusion

🔧🔗https://github.com/poloclub/gam-coach

🔧🔗https://github.com/poloclub/cnn-explainer

Learning Convolutional Neural Networks with Interactive Visualization.

🔧🔗https://github.com/poloclub/webshap

JavaScript library to explain any machine learning models anywhere!

Reasoning Computers. Lambda Calculus, Fully Differentiable. Also Neural Stacks, Queues, Arrays, Lists, Trees, and Latches.